A stochastic analysis of three viral sequences

Area of Science:

• Virology
• Computational Biology
• Genomics

Background:

• Viruses like Kunjin, West Nile, and yellow fever possess a single large open reading frame encoding structural and nonstructural proteins.
• Understanding viral genome organization and evolutionary relationships is crucial for virological research.

Purpose of the Study:

• To analyze and compare the nucleotide sequences of Kunjin, West Nile, and yellow fever viruses.
• To model nucleotide base sequences using nonhomogeneous Markov chains and investigate codon site dependencies.

Main Methods:

• Comparative analysis of nucleotide sequences from three flaviviruses.
• Application of nonhomogeneous Markov chain models to describe nucleotide base sequences.
• Statistical analysis of base mismatches (transitions and transversions) and base usage.

Main Results:

• Kunjin and West Nile viruses exhibit the highest nucleotide sequence similarity.
• Nucleotide sequence matching is strongest at second-position codon sites and weakest at third-position sites.
• Markov chain models provided satisfactory fits, indicating specific dependencies between nucleotide bases at different codon positions.

Conclusions:

• The study elucidates the genetic relatedness of Kunjin, West Nile, and yellow fever viruses.
• Markov chain modeling offers insights into the sequence structure and evolutionary constraints of viral genomes.
• Analyzing codon positions separately resolves inconsistencies in interpreting nucleotide base distribution stationarity.